Physiological Intermolecular Modification Spectroscopy for the Prediction of Response to Anti-Tumor Necrosis Factor Therapy in Patients with Inflammatory Bowel Diseases

Eftekhari, Pierre; Glaubitz, Lisa; Atreya, Raja

doi:10.1159/000358151

Cited by 5 publications

(9 citation statements)

References 37 publications

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“…PIMS takes into account a combination readout based on changes in the resonance of water molecules and macromolecular conformation. PIMS data predicted primary response to anti-TNF therapy with an accuracy of 96% ( 110 ). All mentioned pioneering proteomic pilot study data require validation in larger cohort of patients.…”

Section: Immunological Markersmentioning

confidence: 99%

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

2020

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The advent of anti-TNF agents as the first approved targeted therapy in the treatment of inflammatory bowel disease (IBD) patients has made a major impact on our existing therapeutic algorithms. They have not only been approved for induction and maintenance treatment in IBD patients, but have also enabled us to define and achieve novel therapeutic outcomes, such as combination of clinical symptom control and endoscopic remission, as well as mucosal healing. Nevertheless, approximately one third of treated patients do not respond to initiated anti-TNF therapy and these treatments are associated with sometimes severe systemic side-effects. There is therefore the currently unmet clinical need do establish predictive markers of response to identify the subgroup of IBD patients, that have a heightened probability of response. There have so far been approaches from different fields of IBD research, to descry markers that would empower us to apply TNF-inhibitors in a more rational manner. These markers encompass findings from disease-related and clinical factors, pharmacokinetics, biochemical markers, blood and stool derived parameters, pharmacogenomics, microbial species, metabolic compounds, and mucosal factors. Furthermore, changes in the intestinal immune cell composition in response to therapeutic pressure of anti-TNF treatment have recently been implicated in the process of molecular resistance to these drugs. Insights into factors that determine resistance to anti-TNF therapy give reasonable hope, that a more targeted approach can then be utilized in these non-responders. Here, IL-23 could be identified as one of the key factors determining resistance to TNF-inhibitors. Growing insights into the molecular mechanism of action of TNF-inhibitors might also enable us to derive critical molecular markers that not only mediate the clinical effects of anti-TNF therapy, but which level of expression might also correlate with its therapeutic efficacy. In this narrative review, we present an overview of currently identified possible predictive markers for successful anti-TNF therapy and discuss identified molecular pathways that drive resistance to these substances. We will also point out the necessity and difficulty of developing and validating a diagnostic marker concerning clinically relevant outcome parameters, before they can finally enter daily clinical practice and enable a more personalized therapeutic approach.

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Section: Immunological Markersmentioning

confidence: 99%

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

2020

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“…It provides individual real-time dynamic fingerprints of total physiological macromolecular assemblies in tissue or blood in presence and absence of exogenous molecules (drug or drug candidate, peptide or protein). 13 …”

Section: Methodsmentioning

confidence: 99%

“…PIMS is a near infrared (NIR) spectroscopy method based on the modulation of water molecule resonance, which reflects the change in macromolecular conformation due to the interaction of the compound with its target protein, provided this interaction would lead to activation of related pharmacological signaling pathways. 13 In absence of the latter, there will be no change in water molecule resonance. The NIR bands (at about λ 970–1940 nm) are suited for rapid nondestructive water determination, 20 all shifting a few nm to longer wavelengths (lower frequency) with strengthening of hydrogen bonding due to shifts from high-density water (increasing collapsed structure) to low-density water (increasing expanded structure).…”

Section: Methodsmentioning

confidence: 99%

“…The NIR bands (at about λ 970–1940 nm) are suited for rapid nondestructive water determination, 20 all shifting a few nm to longer wavelengths (lower frequency) with strengthening of hydrogen bonding due to shifts from high-density water (increasing collapsed structure) to low-density water (increasing expanded structure). 13 , 20 , 21 PIMS is therefore able to study protein–protein and protein–solvent interactions in multicomponent solutions. It provides individual real-time dynamic fingerprints of total physiological macromolecular assemblies in a tissue in the presence and absence of exogenous molecules (drug or drug candidates, peptides or proteins).…”

Section: Methodsmentioning

confidence: 99%

“…We have already applied PIMS technology to accurately predict response to subsequent anti-TNF therapy in 30 IBD patients. 13 …”

Section: Introductionmentioning

confidence: 99%

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Functional Molecular Network Analysis Enables Prediction of Response to Vedolizumab Therapy in Anti-TNF Refractory IBD Patients

Eftekhari¹,

Louis²,

Rotoiu

et al. 2020

Crohn's &Amp; Colitis 360

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Background We applied for the first time 2 label-free technologies, physiological intermolecular modulation spectroscopy (PIMS) and nematic protein organization technic (NPOT) in anti-tumor necrosis factor (TNF) refractory inflammatory bowel disease (IBD) patients to identify clinical responders to vedolizumab therapy and elucidate their underlying functional molecular network. Methods PIMS analysis was performed in peripheral blood taken prior to the first vedolizumab application in 20 IBD patients (Crohn disease n = 13; ulcerative colitis n = 7) refractory to at least 1 previous anti-TNF agent therapy. Peripheral blood taken from clinical responders and nonresponders at week 14 of vedolizumab therapy were additionally subjected to NPOT analysis. Response to therapy was assessed by respective clinical disease activity scores (partial Mayo Score and Harvey–Bradshaw Index). Results Clinical response to vedolizumab treatment was observed in 7 of 13 Crohn disease and 4 of 7 ulcerative colitis patients at week 14. Response to therapy was accurately predicted by PIMS blood analysis in 100% of ulcerative colitis and 77% of Crohn disease patients. Overall prediction of clinical response with PIMS blood analysis was achieved with a 89% positive predictive value and a 82% negative predictive value. NPOT analysis revealed the heightened expression of the proteins ITGB7, ITGAV, ITG3, PF4, and ASGH in the peripheral blood of vedolizumab responders compared to nonresponders. Conclusions PIMS analysis of the blood of anti-TNF refractory IBD patients was able to stratify responders to vedolizumab therapy with high accuracy and specificity. NPOT technology could decipher underling molecular networks in the blood of responders, enabling subsequent personalized therapeutic approaches in IBD.

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Novel bio-genetic predictors of response to biologic treatment in inflammatory bowel diseases

Mahajna

Ben‐Horin

2020

Current Opinion in Pharmacology

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Physiological Intermolecular Modification Spectroscopy for the Prediction of Response to Anti-Tumor Necrosis Factor Therapy in Patients with Inflammatory Bowel Diseases

Cited by 5 publications

References 37 publications

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

Personalizing Treatment in IBD: Hype or Reality in 2020? Can We Predict Response to Anti-TNF?

Functional Molecular Network Analysis Enables Prediction of Response to Vedolizumab Therapy in Anti-TNF Refractory IBD Patients

Novel bio-genetic predictors of response to biologic treatment in inflammatory bowel diseases

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